Content-based retrieval of surface defect images with MPEG-7 descriptors

In this paper a prototype system is described for the management and content-based retrieval of defect images in huge image databases. This is a real problem in surface inspection applications, since modern inspection systems may produce up to thousands of defect images in a day. We are using a noncommercial, generic content-based image retrieval (CBIR) system called PicSOM that is modified to fit to the special requirements of our application. The system is tested with a small pre-classified database of surface defect images using the MPEG-7 features. The scalability of the system is also examined using a larger database. Results indicate that the system works with a high level of success.

[1]  Alberto Del Bimbo,et al.  Visual information retrieval , 1999 .

[2]  Teuvo Kohonen,et al.  Self-Organizing Maps , 2010 .

[3]  Ari Visa,et al.  An adaptive texture and shape based defect classification , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[4]  Shih-Fu Chang,et al.  Image Retrieval: Current Techniques, Promising Directions, and Open Issues , 1999, J. Vis. Commun. Image Represent..

[5]  Erkki Oja,et al.  PicSOM - content-based image retrieval with self-organizing maps , 2000, Pattern Recognit. Lett..

[6]  Erkki Oja,et al.  Self-Organising Maps as a Relevance Feedback Technique in Content-Based Image Retrieval , 2001, Pattern Analysis & Applications.

[7]  B. S. Manjunath,et al.  Color and texture descriptors , 2001, IEEE Trans. Circuits Syst. Video Technol..

[8]  Pasi Koikkalainen,et al.  Self-organizing hierarchical feature maps , 1990, 1990 IJCNN International Joint Conference on Neural Networks.

[9]  Jukka Iivarinen,et al.  CONTENT-BASED RETRIEVAL OF DEFECT IMAGES , 2002 .